@phdthesis{Sun2014,
  author    = {Sun, Kaipeng},
  title     = {Six Degrees of Freedom Object Pose Estimation with Fusion Data from a Time-of-flight Camera and a Color Camera},
  isbn      = {978-3-923959-97-6},
  doi       = {10.25972/OPUS-10508},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-105089},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2014},
  abstract  = {Object six Degrees of Freedom (6DOF) pose estimation is a fundamental problem in many practical robotic applications, where the target or an obstacle with a simple or complex shape can move fast in cluttered environments. In this thesis, a 6DOF pose estimation algorithm is developed based on the fused data from a time-of-flight camera and a color camera. The algorithm is divided into two stages, an annealed particle filter based coarse pose estimation stage and a gradient decent based accurate pose optimization stage. In the first stage, each particle is evaluated with sparse representation. In this stage, the large inter-frame motion of the target can be well handled. In the second stage, the range data based conventional Iterative Closest Point is extended by incorporating the target appearance information and used for calculating the accurate pose by refining the coarse estimate from the first stage. For dealing with significant illumination variations during the tracking, spherical harmonic illumination modeling is investigated and integrated into both stages. The robustness and accuracy of the proposed algorithm are demonstrated through experiments on various objects in both indoor and outdoor environments. Moreover, real-time performance can be achieved with graphics processing unit acceleration.},
  subject      = {Mustererkennung},
  language  = {en}
}
@phdthesis{Tzschichholz2014,
  author    = {Tzschichholz, Tristan},
  title     = {Relative pose estimation of known rigid objects using a novel approach to high-level PMD-/CCD- sensor data fusion with regard to applications in space},
  isbn      = {978-3-923959-95-2},
  issn      = {1868-7474},
  doi       = {10.25972/OPUS-10391},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-103918},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2014},
  abstract  = {In this work, a novel method for estimating the relative pose of a known object is presented, which relies on an application-specific data fusion process. A PMD-sensor in conjunction with a CCD-sensor is used to perform the pose estimation. Furthermore, the work provides a method for extending the measurement range of the PMD sensor along with the necessary calibration methodology. Finally, extensive measurements on a very accurate Rendezvous and Docking testbed are made to evaluate the performance, what includes a detailed discussion of lighting conditions.},
  subject      = {Bildverarbeitung},
  language  = {en}
}